Published Aug 2012
Citation
Siebert U, Alagoz O, Bayoumi AM, et al. State-transition modeling: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force-3. Value Health. 2012;15(5):812-820.
Abstract
State-transition modeling is an intuitive, flexible, and transparent approach
of computer-based decision-analytic modeling including both
Markov model cohort simulation and individual-based (first-order
Monte Carlo) microsimulation. Conceptualizing a decision problem in
terms of a set of (health) states and transitions among these states,
state-transition modeling is one of the most widespread modeling
techniques in clinical decision analysis, health technology assessment,
and health-economic evaluation. State-transition models have been
used in many different populations and diseases, and their applications
range from personalized health care strategies to public health
programs. Most frequently, state-transition models are used in the
evaluation of risk factor interventions, screening, diagnostic procedures,
treatment strategies, and disease management programs.
The
goal of this article was to provide consensus-based guidelines for the
application of state-transition models in the context of health care. We
structured the best practice recommendations in the following sections:
choice of model type (cohort vs. individual-level model), model
structure, model parameters, analysis, reporting, and communication.
In each of these sections, we give a brief description, address the issues
that are of particular relevance to the application of state-transition
models, give specific examples from the literature, and provide best
practice recommendations for state-transition modeling. These recommendations
are directed both to modelers and to users of modeling
results such as clinicians, clinical guideline developers, manufacturers,
or policymakers.
Keywords: decision-analytic modeling, guidelines, Markov models,
state-transition modeling.
Copyright © 2017, International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc.
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